import numpy as np
import pandas as pd


TRADING_DAYS_PER_YEAR = 252


def summarize_equity_window(equity: pd.Series, strategy: str, window_years: int | float) -> dict:
    """Summarize a strategy equity curve over a trailing trading-day window."""
    window_days = max(int(window_years * TRADING_DAYS_PER_YEAR), 1)
    clean_equity = equity.dropna()
    if len(clean_equity) < window_days + 1:
        return {
            "strategy": strategy,
            "window_years": window_years,
            "CAGR": np.nan,
            "Sharpe": np.nan,
            "MaxDD": np.nan,
            "TotalRet": np.nan,
        }
    window_equity = clean_equity.tail(window_days + 1)

    daily = window_equity.pct_change(fill_method=None).dropna()
    total_ret = window_equity.iloc[-1] / window_equity.iloc[0] - 1
    years = len(daily) / TRADING_DAYS_PER_YEAR
    cagr = (window_equity.iloc[-1] / window_equity.iloc[0]) ** (1 / years) - 1 if years > 0 else np.nan
    vol = daily.std() * np.sqrt(TRADING_DAYS_PER_YEAR)
    sharpe = (daily.mean() * TRADING_DAYS_PER_YEAR) / vol if vol > 0 else 0.0
    max_dd = (window_equity / window_equity.cummax() - 1).min()
    return {
        "strategy": strategy,
        "window_years": window_years,
        "CAGR": cagr,
        "Sharpe": sharpe,
        "MaxDD": max_dd,
        "TotalRet": total_ret,
    }